Risk Factors and Reoperation Rate in Revision Lumbar Disc Herniation Surgery: A Systematic Review and Meta-Analysis of 1,031,348 Patients
Bibliographic record
Abstract
Study Design A systematic review and meta-analysis. Objectives To estimate reoperation rate after lumbar disc herniation surgery and identify associated risk factors. Methods We searched PubMed, Cochrane Central Register of Controlled Trials (CENTRAL), Web of Science, Scopus, and Embase to April 2025 for English-language randomized controlled trials and observational studies reporting risk factors and reoperation rates. Two reviewers independently screened studies, extracted data, and assessed quality using the Newcastle–Ottawa Scale and Cochrane Risk of Bias 2.0 tool. Meta-analysis used fixed-effect model. Results Twenty-five studies (1,031,348 patients) met the inclusion criteria. The pooled reoperation rate was 8.5% (95% CI: 6.2%-11.6%), rising with follow-up: 4% at ≤1 year, 11.1% at 1-5 years, and 8.8% beyond 5 years ( P < 0.0001 for subgroup differences). Smoking (OR 1.39; 95% CI: 1.09-1.78), older age (OR 1.52; 95% CI: 1.25-1.85), and large annular defect size (OR 2.19; 95% CI: 1.07-4.48) were significant risk factors; sex was not (OR 1.22; 95% CI: 0.96-1.55). Diabetes and certain surgical techniques were also linked to higher risk in individual studies. Adjustment for publication bias increased the overall pooled rate to 10.3% (95% CI: 7.6%-14.0%). Conclusions Reoperation rates after lumbar disc herniation surgery differ by follow-up duration: 4% at ≤1 year, 11.1% at 1-5 years, and 8.8% beyond 5 years. Smoking, older age, diabetes, and large annular defects were significant risk factors. Recognizing high-risk patients can support decisions for extended conservative care or closer follow-up. Further studies should compare revision techniques to improve long-term outcomes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.019 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.042 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".